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Merge pull request #3 from macrocosm-os/features/random-stream
Browse files- README.md +111 -4
- assets/macrocosmos-black.png +0 -0
- assets/macrocosmos-white.png +0 -0
- responses.py +27 -0
- server.py +4 -35
- utils.py +21 -21
- validators/base.py +3 -3
- validators/sn1_validator_wrapper.py +64 -35
README.md
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# chattensor-backend
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Backend for Chattensor app
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## Install
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Create a new python environment and install the dependencies with the command
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```bash
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pip install -r requirements.txt
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```
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> Note: Currently the prompting library is only installable on machines with cuda devices (NVIDIA-GPU).
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<picture>
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<source srcset="./assets/macrocosmos-white.png" media="(prefers-color-scheme: dark)">
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<img src="macrocosmos-white.png">
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</picture>
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<picture>
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<source srcset="./assets/macrocosmos-black.png" media="(prefers-color-scheme: light)">
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<img src="macrocosmos-black.png">
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</picture>
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<br/>
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<br/>
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<br/>
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# Subnet 1 API
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> Note: This project is still in development and is not yet ready for production use.
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The official REST API for Bittensor's flagship subnet 1 ([prompting](https://github.com/opentensor/prompting)), built by [Macrocosmos](https://macrocosmos.ai).
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Subnet 1 is an decentralized open source network containing around 1000 highly capable LLM agents. These agents are capable of performing a wide range of tasks, from simple math problems to complex natural language processing tasks. As subnet 1 is constantly evolving, its capabilities are always expanding. Our goal is to provide a world-class inference engine, to be used by developers and researchers alike.
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This API is designed to power applications and facilitate the interaction between subnets by providing a simple and easy-to-use interface for developers which enables:
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1. **Conversation**: Chatting with the network (streaming and non-streaming)
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2. **Data cleaning**: Filtering empty and otherwise useless responses
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3. **Advanced inference**: Providing enhanced responses using SOTA ensembling techniques (WIP)
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Validators can use this API to interact with the network and perform various tasks.
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To run an API server, you will need a bittensor wallet which is registered as a validator the relevant subnet (1@mainnet or 61@testnet).
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NOTE: At present, miners are choosing not to stream their responses to the network. This means that the server will not be able to provide a streamed response to the client until the miner has finished processing the request. This is a temporary measure and will be resolved in the future.
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## How it works
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The API server is a RESTful API that provides endpoints for interacting with the network. It is a simple [wrapper](./validators/sn1_validator_wrapper.py) around your subnet 1 validator, which makes use of the dendrite to make queries.
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## Install
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Create a new python environment and install the dependencies with the command.
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(First time only)
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```bash
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python3.10 -m venv env
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source env/bin/activate
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pip install -r requirements.txt
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```
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> Note: This project requires python >=3.10.
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> Note: Currently the prompting library is only installable on machines with cuda devices (NVIDIA-GPU).
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## Run
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First activate the virtual environment and then run the following command to start the server:
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```bash
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source env/bin/activate
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```
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Run an API server on subnet 1 with the following command:
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```bash
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EXPECTED_ACCESS_KEY=<ACCESS_KEY> python server.py --wallet.name <WALLET_NAME> --wallet.hotkey <WALLET_HOTKEY> --netuid <NETUID> --neuron.model_id mock --neuron.tasks math --neuron.task_p 1 --neuron.device cpu
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```
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The command ensures that no GPU memory is used by the server, and that the large models used by the incentive mechanism are not loaded.
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> Note: This command is subject to change as the project evolves.
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We recommend that you run the server using a process manager like PM2. This will ensure that the server is always running and will restart if it crashes.
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```bash
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EXPECTED_ACCESS_KEY=<ACCESS_KEY> pm2 start server.py --interpreter python3 --name sn1-api -- --wallet.name <WALLET_NAME> --wallet.hotkey <WALLET_HOTKEY> --netuid <NETUID> --neuron.model_id mock --neuron.tasks math --neuron.task_p 1 --neuron.device cpu
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```
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## API Usage
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At present, the API provides two endpoints: `/chat` (live) and `/echo` (test).
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`/chat` is used to chat with the network and receive a response. The endpoint requires a JSON payload with the following fields:
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- `k: int`: The number of responses to return
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- `timeout: float`: The time in seconds to wait for a response
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- `roles: List[str]`: The roles of the agents to query
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- `messages: List[str]`: The messages to send to the network
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- `prefer: str`: The preferred response to use as the default view. Should be one of `{'longest', 'shortest'}`
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Responses from the `/chat` endpoint are streamed back to the client as they are received from the network. Upon completion, the server will return a JSON response with the following fields:
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- `streamed_chunks: List[str]`: The streamed responses from the network
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- `streamed_chunks_timings: List[float]`: The time taken to receive each streamed response
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- `synapse: StreamPromptingSynapse`: The synapse used to query the network. This contains full context and metadata about the query.
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## Testing
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To test the API locally, you can use the following curl command:
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```bash
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curl --no-buffer -X POST http://0.0.0.0:10000/chat/ -H "api_key: <ACCESS_KEY>" -d '{"k": 5, "timeout": 15, "roles": ["user"], "messages": ["What is today's date?"]}'
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"""
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```
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> Note: Use the `--no-buffer` flag to ensure that the response is streamed back to the client.
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After verifying that the server is responding to requests locally, you can test the server on a remote machine.
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### Troubleshooting
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If you do not receive a response from the server, check that the server is running and that the port is open on the server. You can open the port using the following commands:
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```bash
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sudo ufw allow 10000/tcp
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```
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---
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## Contributing
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If you would like to contribute to the project, please read the [CONTRIBUTING.md](CONTRIBUTING.md) file for more information.
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You can find out more about the project by visiting the [Macrocosmos website](https://macrocosmos.ai) or by joining us in our social channels:
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[](https://substack.com/@macrocosmosai)
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[](https://twitter.com/MacrocosmosAI)
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[](https://twitter.com/MacrocosmosAI)
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[](www.linkedin.com/in/MacrocosmosAI)
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[](https://opensource.org/licenses/MIT)
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assets/macrocosmos-black.png
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assets/macrocosmos-white.png
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responses.py
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from pydantic import BaseModel, Field
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from typing import List, Dict, Any
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class TextStreamResponse(BaseModel):
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streamed_chunks: List[str] = Field(
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default_factory=list, description="List of streamed chunks."
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)
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streamed_chunks_timings: List[float] = Field(
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default_factory=list, description="List of streamed chunks timings, in seconds."
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)
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uid: int = Field(0, description="UID of queried miner")
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completion: str = Field(
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"", description="The final completed string from the stream."
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)
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timing: float = Field(
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0, description="Timing information of all request, in seconds."
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)
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def to_dict(self):
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return {
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"streamed_chunks": self.streamed_chunks,
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"streamed_chunks_timings": self.streamed_chunks_timings,
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"uid": self.uid,
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"completion": self.completion,
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"timing": self.timing,
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}
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server.py
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import utils
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import bittensor as bt
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from aiohttp import web
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from aiohttp.web_response import Response
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from validators import S1ValidatorAPI, QueryValidatorParams, ValidatorAPI
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from middlewares import api_key_middleware, json_parsing_middleware
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```
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curl -X POST http://0.0.0.0:10000/chat/ -H "api_key: hello" -d '{"k": 5, "timeout": 3, "roles": ["user"], "messages": ["hello world"]}'
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curl -X POST http://0.0.0.0:10000/chat/ -H "api_key: hey-michal" -d '{"k": 5, "timeout": 3, "roles": ["user"], "messages": ["on what exact date did the 21st century begin?"]}'
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# stream
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curl --no-buffer -X POST http://129.146.127.82:10000/echo/ -H "api_key: hey-michal" -d '{"k": 3, "timeout": 0.2, "roles": ["user"], "messages": ["i need to tell you something important but first"]}'
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```
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TROUBLESHOOT
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check if port is open
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```
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sudo ufw allow 10000/tcp
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sudo ufw allow 10000/tcp
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```
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# run
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```
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EXPECTED_ACCESS_KEY="hey-michal" pm2 start app.py --interpreter python3 --name app -- --neuron.model_id mock --wallet.name sn1 --wallet.hotkey v1 --netuid 1 --neuron.tasks math --neuron.task_p 1 --neuron.device cpu
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```
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basic testing
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```
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EXPECTED_ACCESS_KEY="hey-michal" python app.py --neuron.model_id mock --wallet.name sn1 --wallet.hotkey v1 --netuid 1 --neuron.tasks math --neuron.task_p 1 --neuron.device cpu
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```
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add --mock to test the echo stream
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"""
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async def chat(request: web.Request) -> Response:
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"""
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Chat endpoint for the validator.
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"""
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return response
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async def echo_stream(request
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return await utils.echo_stream(request_data)
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class ValidatorApplication(web.Application):
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import utils
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import bittensor as bt
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from aiohttp import web
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from validators import S1ValidatorAPI, QueryValidatorParams, ValidatorAPI
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from middlewares import api_key_middleware, json_parsing_middleware
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async def chat(request: web.Request) -> web.StreamResponse:
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"""
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Chat endpoint for the validator.
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"""
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return response
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async def echo_stream(request: web.Request) -> web.StreamResponse:
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return await utils.echo_stream(request)
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class ValidatorApplication(web.Application):
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utils.py
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import re
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import bittensor as bt
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import time
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import json
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from aiohttp import web
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from collections import Counter
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from prompting.rewards import DateRewardModel, FloatDiffModel
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return "qa"
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async def echo_stream(
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k = request_data.get("k", 1)
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exclude = request_data.get("exclude", [])
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timeout = request_data.get("timeout", 0.2)
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message = "\n\n".join(request_data["messages"])
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# Create a StreamResponse
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response = web.StreamResponse(
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status=200, reason="OK", headers={"Content-Type": "
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)
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await response.prepare()
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completion = ""
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# Echo the message k times with a timeout between each chunk
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for _ in range(k):
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for word in message.split():
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chunk = f"{word} "
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await response.write(chunk.encode("utf-8"))
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completion += chunk
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-
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bt.logging.info(f"Echoed: {chunk}")
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completion = completion.strip()
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# Prepare final JSON chunk
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"status_messages": ["Went well!"],
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"status_codes": [200],
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"completion_is_valid": [True],
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"task_name": "echo",
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"ensemble_result": {},
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}
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)
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# Send the final JSON as part of the stream
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await response.write(
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# Finalize the response
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await response.write_eof()
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import re
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import time
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import json
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import asyncio
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import bittensor as bt
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from aiohttp import web
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from responses import TextStreamResponse
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from collections import Counter
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from prompting.rewards import DateRewardModel, FloatDiffModel
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return "qa"
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async def echo_stream(request: web.Request) -> web.StreamResponse:
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request_data = request["data"]
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k = request_data.get("k", 1)
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message = "\n\n".join(request_data["messages"])
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# Create a StreamResponse
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response = web.StreamResponse(
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status=200, reason="OK", headers={"Content-Type": "application/json"}
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)
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await response.prepare(request)
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completion = ""
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chunks = []
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chunks_timings = []
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start_time = time.time()
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# Echo the message k times with a timeout between each chunk
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for _ in range(k):
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for word in message.split():
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chunk = f"{word} "
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await response.write(chunk.encode("utf-8"))
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completion += chunk
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await asyncio.sleep(0.3)
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bt.logging.info(f"Echoed: {chunk}")
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chunks.append(chunk)
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chunks_timings.append(time.time() - start_time)
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completion = completion.strip()
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# Prepare final JSON chunk
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response_data = TextStreamResponse(
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streamed_chunks=chunks,
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streamed_chunks_timings=chunks_timings,
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completion=completion,
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timing=time.time() - start_time,
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).to_dict()
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# Send the final JSON as part of the stream
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await response.write(json.dumps(response_data).encode("utf-8"))
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# Finalize the response
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await response.write_eof()
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validators/base.py
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from abc import ABC, abstractmethod
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from typing import List
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from dataclasses import dataclass
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4 |
-
from aiohttp.web import Response, Request
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5 |
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6 |
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7 |
@dataclass
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@@ -31,10 +31,10 @@ class QueryValidatorParams:
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31 |
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32 |
class ValidatorAPI(ABC):
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33 |
@abstractmethod
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34 |
-
async def query_validator(self, params: QueryValidatorParams) ->
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35 |
pass
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36 |
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37 |
|
38 |
class MockValidator(ValidatorAPI):
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39 |
-
async def query_validator(self, params: QueryValidatorParams) ->
|
40 |
...
|
|
|
1 |
from abc import ABC, abstractmethod
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2 |
from typing import List
|
3 |
from dataclasses import dataclass
|
4 |
+
from aiohttp.web import Response, Request, StreamResponse
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5 |
|
6 |
|
7 |
@dataclass
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|
31 |
|
32 |
class ValidatorAPI(ABC):
|
33 |
@abstractmethod
|
34 |
+
async def query_validator(self, params: QueryValidatorParams) -> StreamResponse:
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35 |
pass
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36 |
|
37 |
|
38 |
class MockValidator(ValidatorAPI):
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39 |
+
async def query_validator(self, params: QueryValidatorParams) -> StreamResponse:
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40 |
...
|
validators/sn1_validator_wrapper.py
CHANGED
@@ -2,7 +2,8 @@ import json
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2 |
import utils
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3 |
import torch
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4 |
import traceback
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5 |
-
import
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6 |
import bittensor as bt
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7 |
from typing import Awaitable
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8 |
from prompting.validator import Validator
|
@@ -12,6 +13,16 @@ from prompting.dendrite import DendriteResponseEvent
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|
12 |
from .base import QueryValidatorParams, ValidatorAPI
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13 |
from aiohttp.web_response import Response, StreamResponse
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14 |
from deprecated import deprecated
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15 |
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16 |
|
17 |
class S1ValidatorAPI(ValidatorAPI):
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@@ -75,27 +86,39 @@ class S1ValidatorAPI(ValidatorAPI):
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|
75 |
return Response(status=500, reason="Internal error")
|
76 |
|
77 |
async def process_response(
|
78 |
-
self, response: StreamResponse,
|
79 |
-
):
|
80 |
"""Process a single response asynchronously."""
|
81 |
-
|
82 |
-
|
83 |
-
|
84 |
-
|
85 |
-
|
86 |
-
|
87 |
-
|
88 |
-
|
89 |
-
|
90 |
-
|
91 |
-
|
92 |
-
|
93 |
-
|
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|
94 |
)
|
95 |
-
|
96 |
-
|
97 |
-
finally:
|
98 |
-
await response.write_eof() # Ensure to close the response properly
|
99 |
|
100 |
async def get_stream_response(self, params: QueryValidatorParams) -> StreamResponse:
|
101 |
response = StreamResponse(status=200, reason="OK")
|
@@ -105,7 +128,7 @@ class S1ValidatorAPI(ValidatorAPI):
|
|
105 |
|
106 |
try:
|
107 |
# Guess the task name of current request
|
108 |
-
task_name = utils.guess_task_name(params.messages[-1])
|
109 |
|
110 |
# Get the list of uids to query for this step.
|
111 |
uids = get_random_uids(
|
@@ -115,6 +138,8 @@ class S1ValidatorAPI(ValidatorAPI):
|
|
115 |
|
116 |
# Make calls to the network with the prompt.
|
117 |
bt.logging.info(f"Calling dendrite")
|
|
|
|
|
118 |
streams_responses = await self.validator.dendrite(
|
119 |
axons=axons,
|
120 |
synapse=StreamPromptingSynapse(
|
@@ -125,13 +150,24 @@ class S1ValidatorAPI(ValidatorAPI):
|
|
125 |
streaming=True,
|
126 |
)
|
127 |
|
128 |
-
|
129 |
-
self.process_response(uid, res)
|
130 |
-
for uid, res in dict(zip(uids, streams_responses))
|
131 |
-
]
|
132 |
-
results = await asyncio.gather(*tasks, return_exceptions=True)
|
133 |
|
134 |
-
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|
|
135 |
except Exception as e:
|
136 |
bt.logging.error(
|
137 |
f"Encountered an error in {self.__class__.__name__}:get_stream_response:\n{traceback.format_exc()}"
|
@@ -144,11 +180,4 @@ class S1ValidatorAPI(ValidatorAPI):
|
|
144 |
return response
|
145 |
|
146 |
async def query_validator(self, params: QueryValidatorParams) -> Response:
|
147 |
-
|
148 |
-
stream = params.request.get("stream", False)
|
149 |
-
|
150 |
-
if stream:
|
151 |
-
return await self.get_stream_response(params)
|
152 |
-
else:
|
153 |
-
# DEPRECATED
|
154 |
-
return await self.get_response(params)
|
|
|
2 |
import utils
|
3 |
import torch
|
4 |
import traceback
|
5 |
+
import time
|
6 |
+
import random
|
7 |
import bittensor as bt
|
8 |
from typing import Awaitable
|
9 |
from prompting.validator import Validator
|
|
|
13 |
from .base import QueryValidatorParams, ValidatorAPI
|
14 |
from aiohttp.web_response import Response, StreamResponse
|
15 |
from deprecated import deprecated
|
16 |
+
from dataclasses import dataclass
|
17 |
+
from typing import List
|
18 |
+
from responses import TextStreamResponse
|
19 |
+
|
20 |
+
|
21 |
+
@dataclass
|
22 |
+
class ProcessedStreamResponse:
|
23 |
+
streamed_chunks: List[str]
|
24 |
+
streamed_chunks_timings: List[float]
|
25 |
+
synapse: StreamPromptingSynapse
|
26 |
|
27 |
|
28 |
class S1ValidatorAPI(ValidatorAPI):
|
|
|
86 |
return Response(status=500, reason="Internal error")
|
87 |
|
88 |
async def process_response(
|
89 |
+
self, response: StreamResponse, async_generator: Awaitable
|
90 |
+
) -> ProcessedStreamResponse:
|
91 |
"""Process a single response asynchronously."""
|
92 |
+
# Initialize chunk with a default value
|
93 |
+
chunk = None
|
94 |
+
# Initialize chunk array to accumulate streamed chunks
|
95 |
+
chunks = []
|
96 |
+
chunks_timings = []
|
97 |
+
|
98 |
+
start_time = time.time()
|
99 |
+
last_sent_index = 0
|
100 |
+
async for chunk in async_generator:
|
101 |
+
if isinstance(chunk, list):
|
102 |
+
# Chunks are currently returned in string arrays, so we need to concatenate them
|
103 |
+
concatenated_chunks = "".join(chunk)
|
104 |
+
new_data = concatenated_chunks[last_sent_index:]
|
105 |
+
|
106 |
+
if new_data:
|
107 |
+
await response.write(new_data.encode("utf-8"))
|
108 |
+
bt.logging.info(f"Received new chunk from miner: {chunk}")
|
109 |
+
last_sent_index += len(new_data)
|
110 |
+
chunks.extend(chunk)
|
111 |
+
chunks_timings.append(time.time() - start_time)
|
112 |
+
|
113 |
+
if chunk is not None and isinstance(chunk, StreamPromptingSynapse):
|
114 |
+
# Assuming the last chunk holds the last value yielded which should be a synapse with the completion filled
|
115 |
+
return ProcessedStreamResponse(
|
116 |
+
synapse=chunk,
|
117 |
+
streamed_chunks=chunks,
|
118 |
+
streamed_chunks_timings=chunks_timings,
|
119 |
)
|
120 |
+
else:
|
121 |
+
raise ValueError("The last chunkis not a StreamPrompting synapse")
|
|
|
|
|
122 |
|
123 |
async def get_stream_response(self, params: QueryValidatorParams) -> StreamResponse:
|
124 |
response = StreamResponse(status=200, reason="OK")
|
|
|
128 |
|
129 |
try:
|
130 |
# Guess the task name of current request
|
131 |
+
# task_name = utils.guess_task_name(params.messages[-1])
|
132 |
|
133 |
# Get the list of uids to query for this step.
|
134 |
uids = get_random_uids(
|
|
|
138 |
|
139 |
# Make calls to the network with the prompt.
|
140 |
bt.logging.info(f"Calling dendrite")
|
141 |
+
start_time = time.time()
|
142 |
+
|
143 |
streams_responses = await self.validator.dendrite(
|
144 |
axons=axons,
|
145 |
synapse=StreamPromptingSynapse(
|
|
|
150 |
streaming=True,
|
151 |
)
|
152 |
|
153 |
+
uid_stream_dict = dict(zip(uids, streams_responses))
|
|
|
|
|
|
|
|
|
154 |
|
155 |
+
random_uid, random_stream = random.choice(list(uid_stream_dict.items()))
|
156 |
+
processed_response = await self.process_response(response, random_stream)
|
157 |
+
|
158 |
+
# Prepare final JSON chunk
|
159 |
+
response_data = json.dumps(
|
160 |
+
TextStreamResponse(
|
161 |
+
streamed_chunks=processed_response.streamed_chunks,
|
162 |
+
streamed_chunks_timings=processed_response.streamed_chunks_timings,
|
163 |
+
uid=random_uid,
|
164 |
+
completion=processed_response.synapse.completion,
|
165 |
+
timing=time.time() - start_time,
|
166 |
+
).to_dict()
|
167 |
+
)
|
168 |
+
|
169 |
+
# Send the final JSON as part of the stream
|
170 |
+
await response.write(json.dumps(response_data).encode("utf-8"))
|
171 |
except Exception as e:
|
172 |
bt.logging.error(
|
173 |
f"Encountered an error in {self.__class__.__name__}:get_stream_response:\n{traceback.format_exc()}"
|
|
|
180 |
return response
|
181 |
|
182 |
async def query_validator(self, params: QueryValidatorParams) -> Response:
|
183 |
+
return await self.get_stream_response(params)
|
|
|
|
|
|
|
|
|
|
|
|
|
|